Human action recognition from various data modalities: A review
Human Action Recognition (HAR) aims to understand human behavior and assign a label to
each action. It has a wide range of applications, and therefore has been attracting increasing …
each action. It has a wide range of applications, and therefore has been attracting increasing …
A review of multimodal human activity recognition with special emphasis on classification, applications, challenges and future directions
Human activity recognition (HAR) is one of the most important and challenging problems in
the computer vision. It has critical application in wide variety of tasks including gaming …
the computer vision. It has critical application in wide variety of tasks including gaming …
Ntu rgb+ d 120: A large-scale benchmark for 3d human activity understanding
Research on depth-based human activity analysis achieved outstanding performance and
demonstrated the effectiveness of 3D representation for action recognition. The existing …
demonstrated the effectiveness of 3D representation for action recognition. The existing …
A guide to convolutional neural networks for computer vision
Computer vision has become increasingly important and effective in recent years due to its
wide-ranging applications in areas as diverse as smart surveillance and monitoring, health …
wide-ranging applications in areas as diverse as smart surveillance and monitoring, health …
View adaptive neural networks for high performance skeleton-based human action recognition
Skeleton-based human action recognition has recently attracted increasing attention thanks
to the accessibility and the popularity of 3D skeleton data. One of the key challenges in …
to the accessibility and the popularity of 3D skeleton data. One of the key challenges in …
Recognizing human actions as the evolution of pose estimation maps
Most video-based action recognition approaches choose to extract features from the whole
video to recognize actions. The cluttered background and non-action motions limit the …
video to recognize actions. The cluttered background and non-action motions limit the …
RGB-D-based human motion recognition with deep learning: A survey
Human motion recognition is one of the most important branches of human-centered
research activities. In recent years, motion recognition based on RGB-D data has attracted …
research activities. In recent years, motion recognition based on RGB-D data has attracted …
A comparative review of recent kinect-based action recognition algorithms
Video-based human action recognition is currently one of the most active research areas in
computer vision. Various research studies indicate that the performance of action …
computer vision. Various research studies indicate that the performance of action …
Spatiotemporal co-attention recurrent neural networks for human-skeleton motion prediction
Human motion prediction aims to generate future motions based on the observed human
motions. Witnessing the success of Recurrent Neural Networks (RNN) in modeling …
motions. Witnessing the success of Recurrent Neural Networks (RNN) in modeling …
Modality distillation with multiple stream networks for action recognition
Diverse input data modalities can provide complementary cues for several tasks, usually
leading to more robust algorithms and better performance. However, while a (training) …
leading to more robust algorithms and better performance. However, while a (training) …